By exploiting multiple antennas at BS (Base Station) or eNodeB, the system throughput can be drastically improved by supporting multiple MSs (Mobile Station) simultaneously. However, the acquisition of the CSIT (Channel State Information at Transmitter) in the base station is critical to achieve the optimal system throughput, but is challenging because CSI (Channel State Information) should be obtained through either the feedback from MSs (in case of FDD and TDD) or the delicate calibration process (in case of TDD). In both FDD and TDD, the feedback of CSI from MSs is necessary and its overhead increases as the number of antennas at the BS increases.
As related arts, to reduce the feedback overhead, several dual structured feedback and the associated precoding schemes have been developed. In the dual structured feedback, the feedback information is composed of two parts—long-term CSIT (mainly, spatial correlation) and short-term CSIT. Accordingly, precoding procedure has two concatenated parts based on long-term CSIT and short-term CSIT.
However, as the number of antennas increases at BS, the feedback overhead becomes more critical problem and the related arts do not consider the case that the BS has an extremely large number of antennas such as Massive MIMO (Multi-Input Multi-Output).